GRU-ODE-Bayes: Continuous modeling of sporadically-observed time series

29 May 2019

Papers citing "GRU-ODE-Bayes: Continuous modeling of sporadically-observed time series"

23 / 173 papers shown

Title
Neural Ordinary Differential Equations for Intervention Modeling Daehoon Gwak Gyuhyeon Sim Michael Poli Stefano Massaroli Jaegul Choo Edward Choi 37 19 0 16 Oct 2020
Vid-ODE: Continuous-Time Video Generation with Neural Ordinary Differential Equation Sunghyun Park Kangyeol Kim Junsoo Lee Jaegul Choo Joonseok Lee Sookyung Kim Edward Choi 21 54 0 16 Oct 2020
A Transformer-based Framework for Multivariate Time Series Representation Learning George Zerveas Srideepika Jayaraman Dhaval Patel A. Bhamidipaty Carsten Eickhoff AI4TS 21 889 0 06 Oct 2020
Cubic Spline Smoothing Compensation for Irregularly Sampled Sequences Jing Shi Jing Bi Yingru Liu Chenliang Xu 6 0 0 03 Oct 2020
Predicting Parkinson's Disease with Multimodal Irregularly Collected Longitudinal Smartphone Data Weijian Li Wei-wei Zhu E. R. Dorsey Jiebo Luo 6 7 0 25 Sep 2020
Adversarial Examples in Deep Learning for Multivariate Time Series Regression Gautam Raj Mode K. A. Hoque AAML AI4TS 23 57 0 24 Sep 2020
Neural Rough Differential Equations for Long Time Series James Morrill C. Salvi Patrick Kidger James Foster Terry Lyons AI4TS 31 124 0 17 Sep 2020
Manifold-adaptive dimension estimation revisited Zsigmond Benkő Marcell Stippinger Roberta Rehus A. Bencze D. Fabó B. Hajnal Loránd Eröss A. Telcs Zoltán Somogyvári 12 10 0 07 Aug 2020
Temporal Pointwise Convolutional Networks for Length of Stay Prediction in the Intensive Care Unit Emma Rocheteau Pietro Lió Stephanie L. Hyland OOD 16 56 0 18 Jul 2020
Learning Differential Equations that are Easy to Solve Jacob Kelly J. Bettencourt Matthew J. Johnson David Duvenaud 30 111 0 09 Jul 2020
Model-based Reinforcement Learning for Semi-Markov Decision Processes with Neural ODEs Jianzhun Du Joseph D. Futoma Finale Doshi-Velez 27 49 0 29 Jun 2020
Lipschitz Recurrent Neural Networks N. Benjamin Erichson Omri Azencot A. Queiruga Liam Hodgkinson Michael W. Mahoney 30 107 0 22 Jun 2020
Understanding Recurrent Neural Networks Using Nonequilibrium Response Theory S. H. Lim 24 16 0 19 Jun 2020
Learning Continuous-Time Dynamics by Stochastic Differential Networks Yingru Liu Yucheng Xing Xuewen Yang Xin Wang Jing Shi Di Jin Zhaoyue Chen BDL 21 6 0 11 Jun 2020
Neural Jump Ordinary Differential Equations: Consistent Continuous-Time Prediction and Filtering Calypso Herrera Florian Krach Josef Teichmann BDL AI4TS 15 30 0 08 Jun 2020
Learning Long-Term Dependencies in Irregularly-Sampled Time Series Mathias Lechner Ramin Hasani AI4TS 22 127 0 08 Jun 2020
Tensorized Transformer for Dynamical Systems Modeling Anna Shalova Ivan Oseledets AI4CE 19 8 0 05 Jun 2020
Synthetic Observational Health Data with GANs: from slow adoption to a boom in medical research and ultimately digital twins? Jeremy Georges-Filteau Elisa Cirillo SyDa AI4CE 36 17 0 27 May 2020
Neural Controlled Differential Equations for Irregular Time Series Patrick Kidger James Morrill James Foster Terry Lyons AI4TS 25 449 0 18 May 2020
Local Lipschitz Bounds of Deep Neural Networks Calypso Herrera Florian Krach Josef Teichmann 14 3 0 27 Apr 2020
Stochastic Latent Residual Video Prediction Jean-Yves Franceschi E. Delasalles Mickaël Chen Sylvain Lamprier Patrick Gallinari VGen 26 159 0 21 Feb 2020
Latent ODEs for Irregularly-Sampled Time Series Yulia Rubanova Ricky T. Q. Chen David Duvenaud BDL AI4TS 31 251 0 08 Jul 2019
Recurrent Neural Networks for Multivariate Time Series with Missing Values Zhengping Che S. Purushotham Kyunghyun Cho David Sontag Yan Liu AI4TS 219 1,897 0 06 Jun 2016